The immune system functions via multiple interactions between many different cell populations. These interactions lead to changes in intracellular protein levels, subcellular localization and activation state, which can have profound effects on both normal and pathological immune system function. Preliminary data has shown that systemic treatment with an anti-CD3 antibody can successfully treat recently hyperglycemic non- obese diabetic mice, resulting in inhibition of beta cell destruction and regeneration of damaged tissue. We hypothesize that the anti-CD3 antibody may act directly on islet infiltrating CD3 lymphocytes, or may activate regulatory T cells. Conventional biochemical techniques are virtually useless in enabling us to look at transient signaling events in rare cell populations in the pancreatic and lymphoid tissues of these mice. With our newly develped 11-color multiparameter flow cytometric analysis for active kinases and phosphoproteins in immune lineages we can take sequential snapshots of the signaling landscape in multiple cell populations. Analysis of this flow cytometry data using our recently developed Bayesian Network Inference algorithms will allow for an unprecedented and rapid determination of the signaling events in autoimmune cell subsets and point to new therapeutic modalities. Our laboratory has developed a set of fluorescent molecular probes that allow us to see how individual cells respond and react to their environment. We will use these probes to analyse cells taken from diabetic mice in order to determine the mechanisms by which the immune system turns against the insulin-producing cells of the pancreas. This will provide information that could point to new targets for drugs to treat diabetes.